Undergraduate AI & Computer Vision Assistant - Student Service

Req Id: 44100

Job Title: Undergraduate AI & Computer Vision Assistant - Student Service

City: W LAFAYETTE

Job Description:

Job Summary

Position Overview Seeking an undergraduate student to support development and testing of AI and image-processing methods for engineering prototypes. The student will work with images, data, probability-based models, and machine-learning tools to help detect, classify, and evaluate physical system states.

What You Will Do

Develop and test image-processing and computer-vision methods using Python.

Work with camera images to identify objects, connections, patterns, and incorrect configurations.

Prepare datasets, label images, extract features, and evaluate model performance.

Experiment with classical computer vision and machine-learning approaches.

Analyze uncertainty and probability in detection and classification results.

Document experiments, results, and technical decisions.

Who Should Apply

Purdue juniors or seniors in Computer Science, Electrical/Computer Engineering, Data Science, Mathematics, Statistics, Mechanical Engineering, or a related field. You do not need to know every topic listed above. Strong mathematical reasoning, curiosity, and willingness to learn matter most.

Education

0

Experience

Useful Background

Python programming and comfort working with data.

Image processing or computer vision, such as OpenCV, filtering, segmentation, feature extraction, or object detection.

Probability and statistics, including random variables, distributions, conditional probability, Bayes rule, expectation, variance, and Markovs inequality.

Linear algebra, including vectors, matrices, transformations, and eigenvalues/eigenvectors.

Calculus and basic optimization concepts.

Interest in stochastic processes and Markov chains, including the Markov property, state transitions, and transition probabilities.

Machine-learning fundamentals such as classification, training/testing data, loss functions, and model evaluation.

Interest and eagerness to learn and work with a diverse team, including virtual work with collaborators in different industry sectors and time zones, building a hands-on kit for a variety of communities of learners.

Helpful, But Not Required

PyTorch, TensorFlow, scikit-learn, NumPy, or pandas.

Convolutional neural networks, object detection, or image classification.

Experience with cameras, embedded systems, robotics, or engineering prototypes.

Coursework in AI, machine learning, computer vision, probability, statistics, signals, or applied mathematics.

FLSA Status

Non-Exempt

Apply now

Posting Start Date: 9/16/26